IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2021)
Soil Moisture Change Monitoring from C and L-band SAR Interferometric Phase Observations
Abstract
The soil moisture changes ($\Delta {{\boldsymbol{M}}_{\boldsymbol{v}}}$) have a significant influence on forestry, hydrology, meteorology, agriculture, and climate change. Interferometric synthetic aperture radar (InSAR), as a potential remote sensing tool for change detection, was relatively less investigated for monitoring this parameter. DInSAR phase (${\boldsymbol{\varphi }}$) is sensitive to the changes in soil moisture (${{\boldsymbol{M}}_{\boldsymbol{v}}}$), and thus, can be potentially used for monitoring $\Delta {{\boldsymbol{M}}_{\boldsymbol{v}}}$. In this article, the relations between ${\boldsymbol{\varphi }}$ and $\Delta {{\boldsymbol{M}}_{\boldsymbol{v}}}$ over wheat, canola, corn, soybean, weed, peas, and bare fields were investigated using an empirical regression technique. To this end, dual-polarimetric C-band Sentinel-1A and quad-polarimetric L-band uninhabited aerial vehicle synthetic aperture radar (UAVSAR) airborne datasets were employed. The regression model showed the coefficient of determination (R2) of 40% to 56% and RMSE of 4.3 vol.% to 6.1 vol.% between the measured and estimated $\Delta {{\boldsymbol{M}}_{\boldsymbol{v}}}$ for different crop types when the temporal baseline ($\Delta {\boldsymbol{T}}$) was very short. As expected, higher accuracies were obtained using UAVSAR given its very short $\Delta {\boldsymbol{T}}$ and its longer wavelength with R2 of 47% to 59% and RMSE of 4.1 vol.% to 6.7 vol.% for different crop types. However, using the Sentinel-1 data with the long $\Delta {\boldsymbol{T}}$ and shorter wavelength (5.6 cm), the accuracies of ${{\bf \Delta }}{{\boldsymbol{M}}_{\boldsymbol{v}}}$ estimations decreased significantly. The results of this study demonstrated that using the ${\boldsymbol{\varphi }}$ information from Sentinel-1 data is a promising approach for monitoring ${{\bf \Delta }}{{\boldsymbol{M}}_{\boldsymbol{v}}}$ at an early growing season or before the crop starts growing, but using L-band SAR data and lower temporal baselines are recommended once the biomass increases.
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